# Build Adaptive Learning Agents

AI agents often repeat weak decisions because they do not retain evaluated reasoning. This skill guides trajectory tracking, verdict scoring, and pattern reuse with AgentDB.

## Install

```bash
npx skillstore add dnyoussef/reasoningbank-adaptive-learning-with-agentdb
```

## Metadata

- Status: approved
- Slug: dnyoussef-reasoningbank-adaptive-learning-with-agentdb
- Version: 1.0.0
- Author version: 1.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: 5aaa089d209fda143a97a821e1ef6bc6d5faf2b84fed7d96f81bf0e0daaba7e1
- Author: DNYoussef
- GitHub username: DNYoussef
- License: MIT
- Repository: https://github.com/DNYoussef/ai-chrome-extension/tree/main/.claude/skills/agentdb/when-implementing-adaptive-learning-use-reasoningbank-agentdb
- Ref: 72d5025b022c77f7a51bdf5c1637c689c80e89d1
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands, network
- Quality score: 80
- Quality tier: silver
- Public page: https://skillstore.pages.dev/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb
- Manifest: https://skillstore.pages.dev/api/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/manifest

## Capabilities

- Defines a five-phase workflow for initializing ReasoningBank with AgentDB.
- Shows how to track agent decisions, reasoning paths, context, outcomes, and timestamps.
- Explains verdict judgment using efficiency, correctness, novelty, reward, and success criteria.
- Describes memory distillation through pattern mining, support thresholds, and confidence thresholds.
- Guides applying learned patterns to future decisions and measuring improvement.

## Use Cases

- Design Self-Improving Agents: Create an agent workflow that records decisions, outcomes, and reasoning paths for later learning.
- Evaluate Agent Decisions: Build verdict criteria that compare efficiency, correctness, novelty, success, and reward across trajectories.
- Mine Reusable Reasoning Patterns: Distill successful trajectories into patterns that can improve future decisions.

## Prompt Templates

### Plan the Setup

```
Use this skill to plan a ReasoningBank and AgentDB setup for my agent. Include trajectory fields, verdict criteria, and success metrics.
```

### Define Trajectory Records

```
Use this skill to design trajectory records for my agent. Include decisions, reasoning, context, outcomes, timestamps, and audit needs.
```

### Design Memory Distillation

```
Use this skill to create a memory distillation plan. Include pattern mining thresholds, pruning rules, confidence scoring, and validation steps.
```

### Build the Learning Loop

```
Use this skill to design an adaptive learning loop that tracks trajectories, judges verdicts, distills patterns, applies learning, and measures improvement.
```

## Limitations

- Assumes ReasoningBank and AgentDB APIs are available in the user environment.
- Provides implementation guidance, not a complete production service.
- Requires users to define domain-specific verdict criteria and safety controls.
- Performance claims depend on data quality, workload, and local infrastructure.

## Best Practices

- Start with clear success metrics before collecting trajectories.
- Separate raw trajectories from distilled patterns so audits stay possible.
- Review verdict criteria with domain experts before using learned patterns.

## Anti Patterns

- Do not treat reward scores as proof of correctness without validation.
- Do not store sensitive user data in trajectories without consent and minimization.
- Do not apply learned patterns to high-risk decisions without human review.

## Security Audit

- Audited at: 2026-07-06T11:24:56.77\+00:00
- Summary: All static command findings are Markdown code fences or TypeScript documentation examples, not shell execution. The hardcoded URLs are reference links, and no prompt injection, exfiltration intent, or unauthorized network behavior was found.

## Stats

- Views: 232
- Downloads: 8
- Favorites: 0
- Popularity score: 0